Demographics

By handedness group

Demographics for included participants, by handedness group (EHI bins).

Handedness N Age (years) Education (years) Sex (M/F/O) EHI
Left 331 28.84 (6.1) 14.45 (2.39) 170/157/4 -81.61 (19.27)
Mixed 135 28.83 (6.17) 14.58 (2.6) 77/56/2 -8.89 (26.49)
Right 378 29.38 (5.93) 14.24 (2.5) 194/178/6 86.01 (16.61)
Left: (EHI <= -40) | Mixed: (-40 < EHI < 40) | Right: (EHI >= 40)


Field x Level

EHI righties (n = 378)

In all EHI-confirmed righties (EHI > 40), do we see the predicted field by level interaction?

Summary. We see the predicted effect, for both reaction time (27.31ms, 95%CI [19.80, 34.82], p < .001) and accuracy (OR = 1.76, 95%CI [1.49, 2.09], p < .001).

Reaction time

Plots

Statistics

Reaction time is modeled as a linear effect of field and level, using data from every target-present trial with a “go” response:

lmer( rt ~ field + level + field:level + (1 | subject) )


Field by level interaction (RT)
ANOVA: compare models with vs. without interaction term
npar AIC BIC logLik deviance Chisq Df p.value
5 622,246.898 622,290.581 −311,118.449 622,236.898 - - -
6 622,198.195 622,250.613 −311,093.097 622,186.195 50.704 1 <.0001


Field by level interaction (RT)
Omnibus F-test
term df sumsq meansq statistic p.value
field 1 10,025.524 10,025.524 0.139 .71
level 1 4,773,142.048 4,773,142.048 66.337 <.0001
field:level 1 2,100,773.834 2,100,773.834 29.197 <.0001
Residuals 45,997 3,309,615,140.279 71,952.848 - -


Field by level interaction (RT)
Compare effect estimate to zero with emmeans()
field_consec level_consec estimate1 SE df2 asymp.LCL3 asymp.UCL3 z.ratio p.value4
LVF - RVF Local - Global 27.308 3.834 Inf 19.793 34.822 7.122 <.0001
1 A positive number means global bias is stronger in LVF (as predicted for right handers)
2 Z-approximation
3 Confidence level: 95%
4 Two-sided


Global bias by field (RT)
contrast estimate1 SE df2 asymp.LCL3 asymp.UCL3 z.ratio p.value4
LVF Local - LVF Global 34.549 2.71 Inf 29.238 39.86 12.75 <.0001
RVF Local - RVF Global 7.242 2.714 Inf 1.922 12.561 2.668 .008
1 A positive number means global bias (faster RT for global)
2 Z-approximation
3 Confidence level: 95%
4 Two-sided, uncorrected


RT estimates by field and level (from model)
field level emmean SE df1 asymp.LCL2 asymp.UCL2
LVF Global 667.092 9.111 Inf 649.234 684.95
LVF Local 701.641 9.119 Inf 683.769 719.514
RVF Global 682.117 9.114 Inf 664.253 699.981
RVF Local 689.359 9.117 Inf 671.489 707.228
1 Z-approximation
2 Confidence level: 95%


RT estimates by field and level (descriptive)
field level median mean SE
LVF Global 622 665.601 2.441
LVF Local 657 699.47 2.558
RVF Global 638 679.765 2.52
RVF Local 650 686.601 2.488


Accuracy

Plots

Statistics

Accuracy is modeled as a binomial effect of field and level, using binary correct/incorrect data from every target-present trial:

glmer( correct ~ field + level + field:level + (1 | subject), family = "binomial" )


Field by level interaction (Accuracy)
ANOVA: compare models with vs. without interaction term
npar AIC BIC logLik deviance Chisq Df p.value
4 17,546.443 17,581.59 −8,769.221 17,538.443 - - -
5 17,507.988 17,551.923 −8,748.994 17,497.988 40.454 1 <.0001


Field by level interaction (Accuracy)
Compare effect estimate to zero with emmeans()
field_consec level_consec odds.ratio1 SE df2 asymp.LCL3 asymp.UCL null z.ratio p.value4
RVF / LVF Local / Global 1.762 0.154 Inf 1.485 2.092 1 6.477 <.0001
1 Backtransformed to odds ratio from log odds ratio (tests are performed on log odds ratio scale). A ratio > 1 means global bias is stronger in the LVF, as predicted for right handers.
2 I don't understand why df is 'Inf' here, but I think it is expected when emmeans does logistic regression. See emmeans FAQ: https://cran.r-project.org/web/packages/emmeans/vignettes/FAQs.html#asymp.
3 Confidence level: 95%
4 Two-sided


Global bias by field (Accuracy)
contrast odds.ratio1 SE df asymp.LCL2 asymp.UCL null z.ratio p.value3
LVF Global / LVF Local 2.312 0.149 Inf 2.037 2.624 1 12.976 <.0001
RVF Global / RVF Local 1.312 0.078 Inf 1.168 1.473 1 4.592 <.0001
1 Backtransformed to odds ratio from log odds ratio (tests are performed on log odds ratio scale). A ratio > 1 means global bias (more correct responses for global).
2 Confidence level: 95%
3 Two-sided, uncorrected


Accuracy estimates by field and level (from model)
field level prob1 SE df asymp.LCL2 asymp.UCL
LVF Global 0.981 0.001 Inf 0.977 0.983
LVF Local 0.956 0.003 Inf 0.95 0.961
RVF Global 0.971 0.002 Inf 0.966 0.974
RVF Local 0.962 0.003 Inf 0.957 0.966
1 Back-transformed to probability (% correct) from logit scale
2 Confidence level: 95%


Accuracy estimates by field and level (descriptive)
field level mean_subject_percent_correct
LVF Global 96.974
LVF Local 93.51
RVF Global 95.527
RVF Local 94.287


EHI mixedies (n = 135)

In all EHI-confirmed mixed handers (-40 < EHI < +40), do we see a field by level interaction?

Summary. We see a smaller effect in the same direction as right handers’ for reaction time (21.66ms, 95%CI [9.26, 34.06], p < .001). For accuracy, we see a smaller, non-significant effect in the same direction as right handers’ (OR = 1.10, 95%CI [0.82, 1.47], p = .53).

Reaction time

Plots

Statistics

Reaction time is modeled as a linear effect of field and level, using data from every target-present trial with a “go” response:

lmer( rt ~ field + level + field:level + (1 | subject) )


Field by level interaction (RT)
ANOVA: compare models with vs. without interaction term
npar AIC BIC logLik deviance Chisq Df p.value
5 221,359.298 221,397.824 −110,674.649 221,349.298 - - -
6 221,349.576 221,395.807 −110,668.788 221,337.576 11.722 1 .0006


Field by level interaction (RT)
Omnibus F-test
term df sumsq meansq statistic p.value
field 1 12,184.492 12,184.492 0.181 .67
level 1 3,074,358.85 3,074,358.85 45.607 <.0001
field:level 1 533,994.492 533,994.492 7.922 .005
Residuals 16,398 1,105,383,522.567 67,409.655 - -


Field by level interaction (RT)
Compare effect estimate to zero with emmeans()
field_consec level_consec estimate1 SE df2 asymp.LCL3 asymp.UCL3 z.ratio p.value4
LVF - RVF Local - Global 21.658 6.325 Inf 9.261 34.055 3.424 .0006
1 A positive number means global bias is stronger in LVF (as predicted for right handers)
2 Z-approximation
3 Confidence level: 95%
4 Two-sided


Global bias by field (RT)
contrast estimate1 SE df2 asymp.LCL3 asymp.UCL3 z.ratio p.value4
LVF Local - LVF Global 37.017 4.474 Inf 28.249 45.785 8.274 <.0001
RVF Local - RVF Global 15.359 4.474 Inf 6.589 24.128 3.433 .0006
1 A positive number means global bias (faster RT for global)
2 Z-approximation
3 Confidence level: 95%
4 Two-sided, uncorrected


RT estimates by field and level (from model)
field level emmean SE df1 asymp.LCL2 asymp.UCL2
LVF Global 620.908 14.561 Inf 592.369 649.447
LVF Local 657.925 14.575 Inf 629.359 686.491
RVF Global 632.664 14.562 Inf 604.124 661.204
RVF Local 648.023 14.574 Inf 619.458 676.587
1 Z-approximation
2 Confidence level: 95%


RT estimates by field and level (descriptive)
field level median mean SE
LVF Global 570 619.02 3.887
LVF Local 603 657.818 4.186
RVF Global 588 631.927 4.019
RVF Local 599 647.899 4.132


Accuracy

Plots

Statistics

Accuracy is modeled as a binomial effect of field and level, using binary correct/incorrect data from every target-present trial:

glmer( correct ~ field + level + field:level + (1 | subject), family = "binomial" )


Field by level interaction (Accuracy)
ANOVA: compare models with vs. without interaction term
npar AIC BIC logLik deviance Chisq Df p.value
4 6,267.227 6,298.256 −3,129.614 6,259.227 - - -
5 6,268.836 6,307.622 −3,129.418 6,258.836 0.392 1 .53


Field by level interaction (Accuracy)
Compare effect estimate to zero with emmeans()
field_consec level_consec odds.ratio1 SE df2 asymp.LCL3 asymp.UCL null z.ratio p.value4
RVF / LVF Local / Global 1.099 0.162 Inf 0.823 1.468 1 0.639 .52
1 Backtransformed to odds ratio from log odds ratio (tests are performed on log odds ratio scale). A ratio > 1 means global bias is stronger in the LVF, as predicted for right handers.
2 I don't understand why df is 'Inf' here, but I think it is expected when emmeans does logistic regression. See emmeans FAQ: https://cran.r-project.org/web/packages/emmeans/vignettes/FAQs.html#asymp.
3 Confidence level: 95%
4 Two-sided


Global bias by field (Accuracy)
contrast odds.ratio1 SE df asymp.LCL2 asymp.UCL null z.ratio p.value3
LVF Global / LVF Local 2.272 0.239 Inf 1.848 2.792 1 7.796 <.0001
RVF Global / RVF Local 2.067 0.214 Inf 1.687 2.533 1 7.004 <.0001
1 Backtransformed to odds ratio from log odds ratio (tests are performed on log odds ratio scale). A ratio > 1 means global bias (more correct responses for global).
2 Confidence level: 95%
3 Two-sided, uncorrected


Accuracy estimates by field and level (from model)
field level prob1 SE df asymp.LCL2 asymp.UCL
LVF Global 0.98 0.003 Inf 0.974 0.985
LVF Local 0.956 0.005 Inf 0.945 0.965
RVF Global 0.979 0.003 Inf 0.973 0.984
RVF Local 0.957 0.005 Inf 0.947 0.966
1 Back-transformed to probability (% correct) from logit scale
2 Confidence level: 95%


Accuracy estimates by field and level (descriptive)
field level mean_subject_percent_correct
LVF Global 96.713
LVF Local 93.148
RVF Global 96.505
RVF Local 93.31


EHI lefties (n = 331)

In all EHI-confirmed lefties (EHI < -40), do we see a field by level interaction?

Summary. We see a smaller effect in the same direction as right handers’ for reaction time (15.64ms, 95%CI [7.58, 23.70], p < .001). For accuracy, we see a larger effect in the same direction as right handers (OR = 1.96, 95%CI [1.63, 2.37], p < .001).

Reaction time

Plots

Statistics

Reaction time is modeled as a linear effect of field and level, using data from every target-present trial with a “go” response:

lmer( rt ~ field + level + field:level + (1 | subject) )


Field by level interaction (RT)
ANOVA: compare models with vs. without interaction term
npar AIC BIC logLik deviance Chisq Df p.value
5 544,097.107 544,140.116 −272,043.553 544,087.107 - - -
6 544,084.643 544,136.254 −272,036.321 544,072.643 14.464 1 .0001


Field by level interaction (RT)
Omnibus F-test
term df sumsq meansq statistic p.value
field 1 3,165,697.487 3,165,697.487 45.987 <.0001
level 1 4,819,463.357 4,819,463.357 70.01 <.0001
field:level 1 748,845.081 748,845.081 10.878 .001
Residuals 40,208 2,767,887,055.586 68,839.212 - -


Field by level interaction (RT)
Compare effect estimate to zero with emmeans()
field_consec level_consec estimate1 SE df2 asymp.LCL3 asymp.UCL3 z.ratio p.value4
LVF - RVF Local - Global 15.643 4.113 Inf 7.582 23.704 3.803 .0001
1 A positive number means global bias is stronger in LVF (as predicted for right handers)
2 Z-approximation
3 Confidence level: 95%
4 Two-sided


Global bias by field (RT)
contrast estimate1 SE df2 asymp.LCL3 asymp.UCL3 z.ratio p.value4
LVF Local - LVF Global 29.357 2.907 Inf 23.66 35.055 10.099 <.0001
RVF Local - RVF Global 13.715 2.915 Inf 8.002 19.427 4.705 <.0001
1 A positive number means global bias (faster RT for global)
2 Z-approximation
3 Confidence level: 95%
4 Two-sided, uncorrected


RT estimates by field and level (from model)
field level emmean SE df1 asymp.LCL2 asymp.UCL2
LVF Global 638.206 9.168 Inf 620.237 656.174
LVF Local 667.563 9.179 Inf 649.572 685.555
RVF Global 663.501 9.172 Inf 645.524 681.478
RVF Local 677.216 9.178 Inf 659.228 695.204
1 Z-approximation
2 Confidence level: 95%


RT estimates by field and level (descriptive)
field level median mean SE
LVF Global 591 637.105 2.476
LVF Local 624 667.612 2.673
RVF Global 621 663.2 2.652
RVF Local 635 676.443 2.67


Accuracy

Plots

Statistics

Accuracy is modeled as a binomial effect of field and level, using binary correct/incorrect data from every target-present trial:

glmer( correct ~ field + level + field:level + (1 | subject), family = "binomial" )


Field by level interaction (Accuracy)
ANOVA: compare models with vs. without interaction term
npar AIC BIC logLik deviance Chisq Df p.value
4 15,377.889 15,412.505 −7,684.944 15,369.889 - - -
5 15,331.656 15,374.927 −7,660.828 15,321.656 48.232 1 <.0001


Field by level interaction (Accuracy)
Compare effect estimate to zero with emmeans()
field_consec level_consec odds.ratio1 SE df2 asymp.LCL3 asymp.UCL null z.ratio p.value4
RVF / LVF Local / Global 1.961 0.188 Inf 1.626 2.366 1 7.04 <.0001
1 Backtransformed to odds ratio from log odds ratio (tests are performed on log odds ratio scale). A ratio > 1 means global bias is stronger in the LVF, as predicted for right handers.
2 I don't understand why df is 'Inf' here, but I think it is expected when emmeans does logistic regression. See emmeans FAQ: https://cran.r-project.org/web/packages/emmeans/vignettes/FAQs.html#asymp.
3 Confidence level: 95%
4 Two-sided


Global bias by field (Accuracy)
contrast odds.ratio1 SE df asymp.LCL2 asymp.UCL null z.ratio p.value3
LVF Global / LVF Local 3.007 0.217 Inf 2.609 3.464 1 15.222 <.0001
RVF Global / RVF Local 1.533 0.096 Inf 1.355 1.734 1 6.799 <.0001
1 Backtransformed to odds ratio from log odds ratio (tests are performed on log odds ratio scale). A ratio > 1 means global bias (more correct responses for global).
2 Confidence level: 95%
3 Two-sided, uncorrected


Accuracy estimates by field and level (from model)
field level prob1 SE df asymp.LCL2 asymp.UCL
LVF Global 0.984 0.001 Inf 0.981 0.986
LVF Local 0.953 0.003 Inf 0.947 0.959
RVF Global 0.972 0.002 Inf 0.968 0.976
RVF Local 0.958 0.003 Inf 0.952 0.963
1 Back-transformed to probability (% correct) from logit scale
2 Confidence level: 95%


Accuracy estimates by field and level (descriptive)
field level mean_subject_percent_correct
LVF Global 97.394
LVF Local 92.995
RVF Global 95.629
RVF Local 93.627